Blog-Kategorien

Faculty of Technology: News - Kategorie Forschung

Professor
Dr. Ulrich Rückert, a researcher at Bielefeld University’s Cluster of
Excellence CITEC and the Faculty of Technology, is working to better
understand the human brain with the help of computer-based models. This
project is taking place throughout the European Union – the goal of
which is to gather findings on the brain and make new connections with
this information.

Professor Dr. Ulrich Rückert is part of the “Human Brain Project.” Photo: CITEC / Bielefeld University

Professor Dr. Ulrich Rückert is part of the “Human Brain
Project.”Professor Dr. Ulrich Rückert is part of the “Human Brain
Project.” Photo: CITEC / Bielefeld UniversityThe brain is not actually
that big, but what it lacks in size, it makes up for in incredible
complexity: “Still today, we don’t know exactly how the brain really
works,” says Professor Dr. Ulrich Rückert, a computer scientist and
engineer who is participating in the “Human Brain Project.” The various
international projects groups working on this research project are
gathering data on the human brain not only to better understand it, but
also to reproduce it in the abstract.

The HBP is set to run for
total of ten years, until 2023. The project is divided into different
subphases: the third (and current) phase will run from 2018–2020, and
the fourth phase is planned for 2020–2023. With each phase, project
groups are required to submit proposals for continued funding. This
project, which Bielefeld University is contributing to, has been
evaluated as “very good” and a total of 1.19 billion Euro has been
budgeted for the EU project.

“We have, relatively speaking, a lot
of detailed knowledge about the brain,” says Rückert, who heads the
“Cognitronics and Sensor Systems” research group at Bielefeld
University’s Faculty of Technology. This research group is also part of
the Cluster of Excellence Cognitive Interaction Technology (CITEC) at
Bielefeld University.

It is clear, for instance, that nerve cells
interact via electrical impulses. “In addition to this, the functions
of individual regions of the brain are also known,” says Rückert. But it
is not clear how the molecular level of the brain relates to its larger
structures. “In this area, there’s still a big gap,” says the engineer.

The
goal of the overarching project is to gather knowledge about the human
brain and forge connections with this information. This knowledge is
meant to serve the fields of medicine and computer science in
particular: if researchers succeed in simulating the brain as accurately
as possible, neurological diseases such as Alzheimer’s or Parkinson’s,
for instance, could be better understood – or perhaps even cured. The
efficacy and side effects of medications could also be tested with
computer-based models.

In HBP, Ulrich Rückert deals with
associative memory, conducting research on neuronal networks. “This is
about developing a new architecture for computers,” he says. Computers
can make things incredibly efficient, such as playing chess or solving
computational tasks. “They are always good when there are set rules and
structures,” says Rückert.

The human brain, however, works in a
completely different way: it is very good at putting different things
together in relationships. “When we go into a room, for example, we know
right away where we are and where we are located in the space,” says
Rückert. “For a computer, on the other hand, this would be a very
complicated computational operation.”

The brain operates under
very different principles than a computer does. “A computer often needs
1000x more energy than the brain for such operations,” says Rückert. “If
we can simulate how the brain works, then the energy usage of technical
systems could be reduced in many areas.” This applies to very different
systems in robotics, such as autonomous driving. “Energy supply has
thus far been a major problem with this,” says Rückert. As he explains,
“one solution could be having certain processes such as orientation run
more energy efficiently.”

The brain is not particularly fast, but
it is efficient in using energy. “For a single operation, a computer is
faster” says Rückert. “But a big strength of the brain is that
different processes run in parallel and are linked with each another.”
In HBP, the models for this are primarily virtual, but they are also
replicated in analog form.

Currently, Rückert has been given the
task of assessing the neuronal models from two research groups in
Heidelberg and Mannheim. “We are working closely together and are having
intensive exchange with the individual groups in the project” says
Rückert. “I’m really looking forward to the results.”

The natural way in which living beings orient themselves and move in
their environment, avoid obstacles, and find their way home again
without their brain consuming much energy is a model for scientists who
also want to equip robots with such complex abilities. Because in this
field there is a wide gulf between the brain and electronics. The
exchange of expertise between behavioural neurologists and robotics
scientists is the focus of a symposium at the FENS Forum 2018 in Berlin
(7.-11.7. 2018).

Bumblebees have a small brain but they cover
considerable distance in the search for food. Depending on the species,
their radius is up to three kilometres. The flight route is teeming
with enemies and obstacles. Changing wind speeds and wind directions add
to the hazards. The insects have to steer their flight through a
changeable environment, navigate extensively and learn how to find a
good source of food and get home to their nests.

"When bumblebees
leave their nest for the first time, they take flights to learn their
surroundings so that they can find their way back," says Dr. Olivier
Bertrand from the Department of Neurobiology at Bielefeld University,
Germany. "These flights have a loop-like pattern, whereby the pattern
varies from animal to animal, as our studies show. We assume that the
bumblebees store snapshots of their environment in their brain, the
usefulness of which is checked on subsequent flights."

When
flying within a complex cluttered environment, bees constantly need to
evaluate the environmental features and have to make decisions that
influence the flight course. Dr. Shridar Ravi from the RMTI University
in Melbourne, Australia, used bumblebees to seek insights into the
mechanisms used for gap identification when the bees are confronted with
an obstacle in their flight path and have to assess gap properties.
Bees spend significant time in the near vicinity of the gap while
performing rapid lateral maneuvers and looking at the gap, as if they
would scan the gap to collect important information. In doing so the bee
could detect the edges of the gap by utilising the difference between
the relative motion of the gap edges and the foreground or background: a
closer object moves relative faster than objects in the background.

As
long as the capabilities of robots are limited, linking the abilities
of animals with those of robots could be helpful. The team led by Prof.
Dr. Noriyasu Ando from the Research Center for Advanced Science and
Technology in Tokyo has taken this path: they have developed an
insect-driven mobile robot. "A male silkmoth sits in a cockpit and his
walking controls the robot

and directs it to a female moth as
soon as he notices her sexual pheromone and reacts to it", is how
Professor Ando describes the principle."From a technical point of
view, this hybrid robot’s performance matches our goal: the future
insect mimetic robot will have the model of the insect brain." The
hybrid robot also provides scientists with insights into the behaviour
of insects. By changing the sensory input and/or the motor output of the
robot, the team was able to uncover the sensory-motor control of the
reactions of silkmoths to odours. "The hybrid robot enables us to
compare an insect brain with an electronic model," said Professor Ando.
"Now the robot is controlled directly by a real silkmoth. If the insect
is replaced by a robot model of this insect, we can directly compare the
performance of the insect brain with that of the model brain on this
robot platform. It's still a conceptual idea, but we're working on it.”

Prof. Dr. Elisabetta Chicca

Neuromorphic systems are similar to the neuronal networks of the brain.
Their hardware is highly specialized and highly interconnected. A team
led by Prof. Dr. Elisabetta Chicca of Bielefeld University has developed
a neuromorphic model that will enable autonomous mobile systems to
navigate better and avoid obstacles in complex environments. The "laser
eyes" (laser rangefinder) of autonomous cars detect obstacles, but are
very expensive despite many years of development. They consume a lot of
energy and - as current incidents have shown - misinterpretations occur
in certain situations. The system of the Bielefeld scientists could
bring progress in this area."We have developed a new electronic
motion detector, the “Spiking Elementary Motion Detector”, which can
detect the relative motion of objects”, says Professor Chicca. Every car
or train driver knows what a "relative movement" is: the church tower
in the distance glides slowly past, while the tree at the roadside
rushes very quickly past. Insects use such information during navigation
in the terrain to avoid collisions.The new motion detector, sEMD
for short, is a technical nerve cell with an artificial synapse. It can
pick up signals and produce signals when two pulses arrive within a
certain time - hence the name suffix "spiking". A chip can carry
thousands of these detectors, depending on the experiment.

The
detectors receive their input from innovative neuromorphic cameras,
developed by a company in switzerland. In contrast to normal cameras,
the pixels of the sensors in these cameras only produce a signal
independently if something changes in their "field of vision". These
signals are picked up by the motion detector's receptive fields. Each
detector has two receptive fields, each receiving signals from nine
pixels. If more than half of the pixels of a receptive field are
activated, the receptive field produces a signal that is further
processed by the detector. The detector can calculate the relative speed
at which an object moves in front of the camera based on the time
intervals between the signals of two adjacent receptive fields. "Our
experiments show that it is possible to generate information for the
navigation of robots that avoid collisions," explains Professor Chicca.
"Our results pave the way for the construction of low-power compact
systems for autonomous navigation. In addition, the sEMD is a
universally applicable element for calculating time differences and can
therefore also be used for processing other sensory stimuli, for example
for locating the source of a sound.

A
team of students and researchers from the Cluster of Excellence
Cognitive Interaction Technology (CITEC) at Bielefeld University won the
RoboCup World Championship in Montreal, Canada. RoboCup is the leading,
and largest, competition for intelligent robots in the world. The “Team
of Bielefeld” (ToBi) showed its skills with Pepper the robot in the
household service league. More than 400 teams from around the world
competed in the various leagues of the competition from 18-22 June 2018.
The researchers are now back in Bielefeld.

The
CITEC team earned first place with Pepper in the household service
league of the RoboCup World Championship. Photo: Bielefeld
University/CITEC

Dr. Sven Wachsmuth, who heads the
CITEC Central Labs, and his research associate Florian Lier led the
team, together with Master’s student Johannes Kummert. “It’s fantastic
to see how the students have progressed from the first preparations to
the competition,” says Wachsmuth. “They learned to deal with complex
systems like robots, and to work independently with them. That we were
then able to take first place is, of course, a great success.”

Lier
adds: “The team prepared itself very well, also for dealing with
uncertainties. The infrastructure there is different from that in the
lab. The students put a lot of work into making the software as stable
as possible, and they succeeded in this.”

In the household
service league RoboCup@Home, their robot had to master various assistive
tasks as precisely as possible, including working as a waiter, bringing
groceries into the home, loading a dishwasher, giving visitors an
introductory tour of RoboCup, and finding its way in unfamiliar
surroundings. The CITEC team competed in the Social Standard Platform
League (SSPL), a subleague of the household service league. In the SSPL,
teams only compete with Pepper, a robot produced by the company
Softbank. Second place went to the team from Australia, where the next
RoboCup competition will be held, and the team from Chile took third
place.

Student Janneke Simmering from the CITEC team took part in
the robot world championship for the first time. “The exciting question
was: will the robot do what it’s supposed to do? We spent four weeks
programming the software and tried to prepare for as many factors and
eventualities as possible. The work paid off, and that’s a great
feeling. We’re celebrating now.”

Members of this year’s team
included: Robert Feldhans, Felix Friese, Kai Konen, David Leins, Jan
Patrick Nülle, Sarah Schröder, Janneke Simmering, Philipp von
Neumann-Cosel, Johannes Kummert, Florian Lier and Sven Wachsmuth. The
preparations for RoboCup are incorporated into a university seminar –
each year, new students from the course work together in the team. The
Cluster of Excellence Cognitive Interaction Technology (CITEC) has
participated in RoboCup since 2009. In 2016, the team earned the title
of world champion for the first time, and the team has also taken third
place a total of three times: 2012, in Mexico; 2015, in China; and 2017,
in Japan.

The Cluster of Excellence Cognitive Interaction
Technology (CITEC) at Bielefeld University is one of 43 clusters of
excellence in Germany, and the only cluster with a focus in robotics.
CITEC is working to make technical systems intuitive and easy to
operate. CITEC’s interdisciplinary approach combines cognitive research
with technology. Since 2007, CITEC has been funded as part of the
Excellence Initiative of the German federal and state governments.
Approximately 250 researchers work at the Cluster.

Professor Dr. Ellen Baake (56) has been appointed for five years
to the Board of the European Society of Mathematical and
Theoretical Biology (European Society of Mathematical and Theoretical
Biology, ESMTB). Task of the ESMTB is the promotion
of theoretical approaches and mathematical methods in the
Life sciences worldwide and in Europe. The society organizes
and supports conferences and summer schools on an international level
and in 2018 co-ordinates diverse activities for the "Year of
Mathematical Biology ". Ellen Baake leads the working group
Biomathematics and Theoretical Bioinformatics at the Faculty of Engineering
the University of Bielefeld. Since 2006 she is the spokeswoman for
Research Center Mathematical Modeling and since 2011 coordinated the the priority program "Probabilistic
Structures in Evolution "of the German Research Foundation (DFG).